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Updated: Aug 19, 2026
Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 3, 2013
Risk-Based Selection for Active Surveillance: Results of the Movember Foundation's Global Action Plan Prostate Cancer
Sophie M Bruinsma1, Daan Nieboer1,2, Monique J Roobol1
1Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands.
Purpose:
We sought to identify and validate known predictors of disease reclassification at 1 or 4 years to support risk-based selection of patients suitable for active surveillance.
Materials And Methods:
An individual participant data meta-analysis using data from 25 established cohorts within the Movember Foundations GAP3 Consortium. In total 5,530 men were included. Disease reclassification was defined as any increase in Gleason grade group at biopsy at 1 and 4 years. Associations were estimated using random effect logistic regression models. The discriminative ability of combinations of predictors was assessed in an internal-external validation procedure using the AUC curve.
Results:
Among the 5,570 men evaluated at 1 year, we found 815 reclassifications to higher Gleason grade group at biopsy (pooled reclassification rate 13%, range 0% to 31%). Important predictors were age, prostate specific antigen, prostate volume, T-stage and number of biopsy cores with prostate cancer. Among the 1,515 men evaluated at 4 years, we found 205 reclassifications (pooled reclassification rates 14%, range 3% to 40%), with similar predictors. The average areas under the receiver operating characteristic curve at internal-external validation were 0.68 and 0.61 for 1-year and 4-year reclassification, respectively.
Conclusions:
Disease reclassification occurs typically in 13% to 14% of biopsies at 1 and 4 years after the start of active surveillance with substantial between-study heterogeneity. Current guidelines might be extended by considering prostate volume to improve individualized selection for active surveillance. Additional predictors are needed to improve patient selection for active surveillance.
